scholarly journals Projection Algorithms for Variational Inclusions

2012 ◽  
Vol 2012 ◽  
pp. 1-11
Author(s):  
Youli Yu ◽  
Pei-Xia Yang ◽  
Khalida Inayat Noor
Keyword(s):  
Hilbert Space ◽  
Variational Inequality ◽  
Iterative Algorithm ◽  
Real Hilbert Space ◽  
Projection Algorithm ◽  
Variational Inclusion ◽  
Inclusion Problem ◽  
Variational Inclusions ◽  
Projection Algorithms ◽  
Variational Inclusion Problem

We present a projection algorithm for finding a solution of a variational inclusion problem in a real Hilbert space. Furthermore, we prove that the proposed iterative algorithm converges strongly to a solution of the variational inclusion problem which also solves some variational inequality.

scholarly journals An Iterative Method for Solving Split Monotone Variational Inclusion Problems and Finite Family of Variational Inequality Problems in Hilbert Spaces

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Wanna Sriprad ◽  
Somnuk Srisawat
Keyword(s):  
Variational Inequality ◽  
Real Hilbert Space ◽  
Finite Family ◽  
Variational Inequality Problems ◽  
Variational Inclusion ◽  
Common Element ◽  
Strong Convergence Theorem ◽  
Inclusion Problem ◽  
Variational Inclusion Problem ◽  
Convex Minimization Problems

The purpose of this paper is to study the convergence analysis of an intermixed algorithm for finding the common element of the set of solutions of split monotone variational inclusion problem (SMIV) and the set of a finite family of variational inequality problems. Under the suitable assumption, a strong convergence theorem has been proved in the framework of a real Hilbert space. In addition, by using our result, we obtain some additional results involving split convex minimization problems (SCMPs) and split feasibility problems (SFPs). Also, we give some numerical examples for supporting our main theorem.

scholarly journals An inertial iterative scheme for solving variational inclusion with application to Nash-Cournot equilibrium and image restoration problems

2021 ◽  
Vol 37 (3) ◽  
pp. 361-380
Author(s):  
JAMILU ABUBAKAR ◽  
◽  
POOM KUMAM ◽  
ABOR ISA GARBA ◽  
MUHAMMAD SIRAJO ABDULLAHI ◽  
...  
Keyword(s):  
Variational Inequality ◽  
Image Restoration ◽  
Split Feasibility Problem ◽  
Variational Inclusion ◽  
Feasibility Problem ◽  
Inclusion Problem ◽  
Relaxation Techniques ◽  
Cournot Equilibrium ◽  
Monotone Equations ◽  
Variational Inclusion Problem

Variational inclusion is an important general problem consisting of many useful problems like variational inequality, minimization problem and nonlinear monotone equations. In this article, a new scheme for solving variational inclusion problem is proposed and the scheme uses inertial and relaxation techniques. Moreover, the scheme is self adaptive, that is, the stepsize does not depend on the factorial constants of the underlying operator, instead it can be computed using a simple updating rule. Weak convergence analysis of the iterates generated by the new scheme is presented under mild conditions. In addition, schemes for solving variational inequality problem and split feasibility problem are derived from the proposed scheme and applied in solving Nash-Cournot equilibrium problem and image restoration. Experiments to illustrate the implementation and potential applicability of the proposed schemes in comparison with some existing schemes in the literature are presented.

scholarly journals A new iterative algorithm for solving general variational inclusion problem with application

2021 ◽  
Author(s):  
M. Akram ◽  
A.F. Aljohani ◽  
M. Dilshad ◽  
Aysha Khan
Keyword(s):  
Differential Equation ◽  
Iterative Algorithm ◽  
Delay Differential Equation ◽  
Iterative Algorithms ◽  
Convergence Result ◽  
Variational Inclusion ◽  
Inclusion Problem ◽  
Numerical Example ◽  
Variational Inclusion Problem ◽  
Delay Differential

In this paper, we pose a new iterative algorithm and show that this newly constructed algorithm converges faster than some existing iterative algorithms. We validate our claim by an illustrative example. Also, we discuss the convergence of our algorithm to approximate the solution of a general variational inclusion problem. Also, we present a numerical example to verify our existence and convergence result. Finally, we apply our proposed iterative algorithm to solve a delay differential equation as an application

scholarly journals Hybrid Iterative Scheme for Triple Hierarchical Variational Inequalities with Mixed Equilibrium, Variational Inclusion, and Minimization Constraints

2014 ◽  
Vol 2014 ◽  
pp. 1-22
Author(s):  
Lu-Chuan Ceng ◽  
Cheng-Wen Liao ◽  
Chin-Tzong Pang ◽  
Ching-Feng Wen
Keyword(s):  
Variational Inequality ◽  
Real Hilbert Space ◽  
Nonexpansive Mappings ◽  
Solution Set ◽  
Steepest Descent Method ◽  
Projection Algorithm ◽  
Generalized Mixed Equilibrium Problem ◽  
Common Element ◽  
Variational Inclusions ◽  
Mixed Equilibrium

We introduce and analyze a hybrid iterative algorithm by combining Korpelevich's extragradient method, the hybrid steepest-descent method, and the averaged mapping approach to the gradient-projection algorithm. It is proven that, under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of finitely many nonexpansive mappings, the solution set of a generalized mixed equilibrium problem (GMEP), the solution set of finitely many variational inclusions, and the solution set of a convex minimization problem (CMP), which is also a unique solution of a triple hierarchical variational inequality (THVI) in a real Hilbert space. In addition, we also consider the application of the proposed algorithm to solving a hierarchical variational inequality problem with constraints of the GMEP, the CMP, and finitely many variational inclusions.

scholarly journals Modified subgradient extragradient method for system of variational inclusion problem and finite family of variational inequalities problem in real Hilbert space

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Araya Kheawborisut ◽  
Atid Kangtunyakarn
Keyword(s):  
Hilbert Space ◽  
Variational Inequalities ◽  
Real Hilbert Space ◽  
Extragradient Method ◽  
Finite Family ◽  
Variational Inclusion ◽  
Common Element ◽  
Inclusion Problem ◽  
Subgradient Extragradient Method ◽  
Generalized System

AbstractFor the purpose of this article, we introduce a modified form of a generalized system of variational inclusions, called the generalized system of modified variational inclusion problems (GSMVIP). This problem reduces to the classical variational inclusion and variational inequalities problems. Motivated by several recent results related to the subgradient extragradient method, we propose a new subgradient extragradient method for finding a common element of the set of solutions of GSMVIP and the set of a finite family of variational inequalities problems. Under suitable assumptions, strong convergence theorems have been proved in the framework of a Hilbert space. In addition, some numerical results indicate that the proposed method is effective.

scholarly journals A modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces

2020 ◽  
Vol 2020 (1) ◽  
pp. 28-39
Author(s):  
Thierno M. M. Sow
Keyword(s):  
Iterative Algorithm ◽  
Hilbert Spaces ◽  
Proximal Point Algorithm ◽  
Variational Inclusion ◽  
Inclusion Problem ◽  
Proximal Point ◽  
Inclusion Problems ◽  
Common Solution ◽  
Variational Inclusion Problem ◽  
The Common

AbstractThe purpose of this paper is to use a modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces. It is proven that the sequence generated by the proposed iterative algorithm converges strongly to the common solution of the convex minimization and variational inclusion problems.

scholarly journals Convergence Analysis of a Three-Step Iterative Algorithm for Generalized Set-Valued Mixed-Ordered Variational Inclusion Problem

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 444
Author(s):  
Praveen. Agarwal ◽  
Doaa Filali ◽  
M. Akram ◽  
M. Dilshad
Keyword(s):  
Iterative Algorithm ◽  
Hilbert Spaces ◽  
Resolvent Operator ◽  
Variational Inclusion ◽  
Inclusion Problem ◽  
Existence And Uniqueness Results ◽  
Variational Inclusion Problem ◽  
Uniqueness Results ◽  
Convergence Results ◽  
The Resolvent Operator

This manuscript aims to study a generalized, set-valued, mixed-ordered, variational inclusion problem involving H(·,·)-compression XOR-αM-non-ordinary difference mapping and relaxed cocoercive mapping in real-ordered Hilbert spaces. The resolvent operator associated with H(·,·)-compression XOR-αM-non-ordinary difference mapping is defined, and some of its characteristics are discussed. We prove existence and uniqueness results for the considered generalized, set-valued, mixed-ordered, variational inclusion problem. Further, we put forward a three-step iterative algorithm using a ⊕ operator, and analyze the convergence of the suggested iterative algorithm under some mild assumptions. Finally, we reconfirm the existence and convergence results by an illustrative numerical example.

scholarly journals Two self-adaptive inertial projection algorithms for solving split variational inclusion problems

2021 ◽  
Vol 7 (4) ◽  
pp. 4960-4973
Author(s):  
Zheng Zhou ◽  
◽  
Bing Tan ◽  
Songxiao Li
Keyword(s):  
Hilbert Spaces ◽  
Variational Inclusion ◽  
Inclusion Problem ◽  
Projection Algorithms ◽  
Approximation Solution ◽  
Inclusion Problems ◽  
Variational Inclusion Problem ◽  
Adaptive Stepsize ◽  
The Given ◽  
Self Adaptive

<abstract><p>This paper is to analyze the approximation solution of a split variational inclusion problem in the framework of Hilbert spaces. For this purpose, inertial hybrid and shrinking projection algorithms are proposed under the effect of a self-adaptive stepsize which does not require information of the norms of the given operators. The strong convergence properties of the proposed algorithms are obtained under mild constraints. Finally, a numerical experiment is given to illustrate the performance of proposed methods and to compare our algorithms with an existing algorithm.</p></abstract>

Sign in / Sign up

Export Citation Format

Share Document